SINGAPORE: A new five-year programme will extend Singapore MRT automation beyond train operations, exploring highly automated depots, AI-assisted predictive maintenance and drone-based infrastructure inspections across the network.

An SMRT train at Boon Lay station on Singapore’s East–West Line.
A C151B MRT train at Boon Lay station; illustrative image, not the current research announcement. Photo: Seloloving, CC BY-SA 4.0.

The direction was discussed in Parliament on 7 July 2026. It remains a research and development programme rather than an order to convert named facilities. Under the RIE2030 framework, the government will study next-generation autonomous mass-transit technology and highly automated rail depots; it has not identified the first depots or published an implementation timetable.

Singapore will invest S$800 million, quoted in the supplied report as EUR 542.12 million, in transport and connectivity research over five years. According to the Ministry of Transport’s funding announcement, the commitment is more than double the previous programme, and about two-thirds will support autonomy and digital-twin capabilities across land, air and sea transport. The S$800 million is therefore not a rail-only allocation.

Singapore MRT automation shifts work inside depots

The rail component will examine how AI and sensors can support predictive maintenance and automate labour-intensive tasks. Digital systems could inspect trains, prepare them for service and flag potential faults earlier, while technicians concentrate on complex interventions that still require experience and judgement.

Smart sensors and drones have already been deployed for routine rail and road infrastructure inspections, the government said in its official explanation of AI and transport jobs. These tools can collect images and condition data without sending staff into every trackside or hard-to-reach location. Over time, such data could support maintenance based on an asset’s observed condition rather than fixed intervals alone.

For commuters, the stated objective is more reliable service and faster recovery from disruptions. Those benefits remain targets: the government has not announced performance figures, a completion date or the individual MRT depots that would receive the technology first.

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Training plans accompany automated maintenance

Singapore’s policy frames automation as a change in job content rather than an immediate removal of rail staff. Repetitive manual work is expected to decline, while demand grows for capabilities in software, robotics, data analysis, automated-system maintenance and control-centre operations.

The workforce plan includes structured attachments with rail operators for students in ITE’s Higher NITEC in Rapid Transit Engineering, alongside stronger links between transport companies and institutes of higher learning. The aim is to give students direct experience with operators and engineers before graduation.

The wider transport sector contributes about 10% of Singapore’s GDP and around 7% of all jobs across aviation, maritime, logistics and land transport. Funding applications under RIE2030 will be open to institutes of higher learning and research institutes, while companies may participate through collaborations; further application details are due during the funding tranche.

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